Makeup evaluation system and operating method thereof

ABSTRACT

A makeup evaluation system can include a mobile terminal for photographing an image and transmitting the photographed image to a makeup server; and a makeup server including a make-up DB management unit for storing at least one algorithm used for make-up evaluation, a region detection unit for detecting a face region in the photographed image, a makeup analysis unit for evaluating makeup by applying the stored algorithm to the detected face region, and a wireless communication unit for transmitting an evaluation result signal including information on the result of evaluating the makeup to the mobile terminal, in which the mobile terminal displays the evaluation result according to a received evaluation result signal, and the makeup server evaluates makeup by applying different algorithms for each face region.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.16/482,511, filed on Jul. 31, 2019, which is the National Phase of PCTInternational Application No. PCT/KR2018/001412, filed on Feb. 1, 2018,which claims priority under 35 U.S.C. 119(a) to Patent Application Nos.10-2017-0014403, filed in the Republic of Korea on Feb. 1, 2017, and10-2018-0012931, filed in the Republic of Korea on Feb. 1, 2018, all ofthese applications being hereby expressly incorporated by reference intothe present application.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to a makeup evaluation system and anoperating method thereof.

Discussion of the Related Art

Recently, a user's interest in cosmetics, makeup, etc. is increasingaccording to the development of beauty industry. Accordingly, the user'sneeds for cosmetics, makeup, and the like tend to be diversified.

Meanwhile, since each individual user has various skin colors, faceshapes, features, etc., makeup suited for the individual user may bedifferent. Thus, the user may have difficulty in selecting makeup suitedfor himself/herself. The user may be wondering whether the makeup iswell done after the makeup, or which parts should be complemented.

Recently, in accordance with such a trend, applications for applyingvirtual makeup to a user's face have been developed. In this case,although they may cause curiosity and interest of the user, there is alimit that an individual has to decide which makeup is suitable for theuser. That is, it is difficult to provide customized services forindividual users. For example, in a case of a beauty service currentlyprovided, the collaboration of makeup specialists is not included, oreven if there is collaboration of makeup specialists, it may be based onlimited data. Therefore, there are difficulties in providing customizedservices to individual users.

Meanwhile, recently, application fields of machine learning (ML)technology, especially deep learning (DL) technology, have beenexpanded.

ML technology is a technology that may extract features through a lot ofdata, and when new data is input, a computer may classify itselfaccording to features.

DL technology is a part of ML technology. DL technology which is basedon artificial neural networks (ANN) for constructing artificialintelligence, refers to a technology in which a computer classifies databy finding patterns from big data as if human beings distinguish things.

A customized makeup may be provided to a user based on more objectivedata by applying DL technology to a makeup service.

SUMMARY OF THE INVENTION

The present invention is directed to providing a makeup evaluationsystem and an operating method thereof for evaluating makeup of a user.

The present invention is directed to providing a makeup evaluationsystem and an operation method thereof that provides excellence ofmakeup in numerical values by analyzing makeup in a photograph.

More specifically, the present invention is directed to providing amakeup evaluation system and an operation method thereof for evaluatingmakeup through reliable score data based on an evaluation of a makeupspecialist.

The present invention is directed to providing a makeup evaluationsystem and an operation method thereof, which is constructing a databasefor automatically evaluating makeup through machine learning technology.

The present invention is directed to providing a makeup evaluationsystem and an operation method thereof for evaluating makeup for eachpart of a user's face.

A makeup evaluation system according to an embodiment of the presentinvention includes a mobile terminal for photographing a facial imageand transmitting the photographed facial image to a makeup server, andthe makeup server for storing makeup score data and, when receiving thefacial image from the mobile terminal, detecting at least one faceregion in the facial image, calculating a makeup score for each of thedetected face regions on the basis of the makeup score data, andtransmitting the calculated makeup score to the mobile terminal, whereinthe makeup server, when receiving a makeup theme from the mobileterminal, calculates an makeup score according to the makeup theme, andthe makeup score may be calculated differently according to a shape ofthe detected face region and the makeup theme.

According to an embodiment of the present invention, it is possible toprovide a user with a more reliable makeup evaluation service.Specifically, according to the embodiment of the present invention, itis possible to provide a makeup evaluation service similar to anevaluation of a makeup specialist.

According to an embodiment of the present invention, there is anadvantage that makeup may be evaluated by detecting each region of aface and applying an algorithm. More specifically, since a size, ashape, and the like of the face are different for each user, even if thesame makeup is performed, there are a person who is suitable for themakeup and a person who is not suitable therefor. Therefore, accordingto the present invention, makeup evaluation considering facecharacteristics of a user may be performed by extracting a region ofeach face part and applying the algorithm to the extracted region, andthus there is an advantage that a precise makeup evaluation may beperformed.

According to an embodiment of the present invention, there is anadvantage that it is possible to evaluate whether makeup is good or notfor each corresponding part by extracting a region of each face part andapplying different algorithms to each extracted region and it ispossible to evaluate an overall makeup score of each face part.

According to an embodiment of the present invention, there is anadvantage that it is possible to more accurately recognize a face regionby using an RGB value of a region of each face part.

According to an embodiment of the present invention, since makeup isevaluated by using a Lab value showing the same value regardless ofcharacteristics of a display unit, there is an advantage that anobjective makeup evaluation may be performed regardless of an evaluationmedium such as a model of a mobile terminal.

According to an embodiment of the present invention, there is anadvantage that it is also possible to perform detailed makeup evaluationsuch as hue harmony and color uniformity in addition to simplyevaluating a color of makeup.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a configuration of a makeupevaluation system according to an embodiment of the present invention.

FIG. 2 is a block diagram for describing a mobile terminal according toan embodiment of the present invention.

FIG. 3 is a block diagram for describing a makeup server according to afirst embodiment of the present invention.

FIG. 4 is a ladder diagram illustrating an operation method of a makeupevaluation system according to the first embodiment of the presentinvention.

FIG. 5 is an illustrative view for describing a method of receivingimage data by the makeup server according to the first embodiment of thepresent invention.

FIG. 6 is an illustrative view for describing a makeup score dataaccording to the first embodiment of the present invention.

FIGS. 7 and 8 are illustrative views for describing a method of tuningthe makeup score data according to the first embodiment of the presentinvention.

FIG. 9 is a view for describing a makeup evaluation database generatedaccording to the first embodiment of the present invention.

FIG. 10 is an illustrative view for describing a screen for transmittinga request signal of a makeup evaluation according to the firstembodiment of the present invention.

FIG. 11 is an illustrative view for describing a method of analyzing afacial image by the makeup server according to the first embodiment ofthe present invention.

FIG. 12 is an illustrative view for describing a method of analyzing afacial image by a makeup analysis unit according to the first embodimentof the present invention.

FIG. 13 is an illustrative view for describing a regenerated makeupevaluation database according to the first embodiment of the presentinvention.

FIGS. 14A and 14B are illustrative views for describing a makeup scorescreen according to the first embodiment of the present invention.

FIG. 15 is a view for describing an effect of a makeup theme on a makeupevaluation according to the first embodiment of the present invention.

FIG. 16 is a view for describing a score window by region according tothe first embodiment of the present invention.

FIG. 17 is a view for describing a makeup balance evaluation accordingto the first embodiment of the present invention.

FIG. 18 is a view for describing a no makeup evaluation result accordingto the first embodiment of the present invention.

FIG. 19 is a block diagram for describing a makeup server according to asecond embodiment of the present invention.

FIG. 20 is a ladder diagram illustrating a method of operating a makeupevaluation system according to the second embodiment of the presentinvention.

FIGS. 21 to 25 are views for describing an evaluation algorithm appliedto an eyebrow part evaluation according to the second embodiment of thepresent invention.

FIG. 26 is an illustrative view for describing a method of displaying anevaluation result of an eyebrow part according to the second embodimentof the present invention.

FIGS. 27 and 28 are views for describing an evaluation algorithm appliedto a dark circle part evaluation according to the second embodiment ofthe present invention.

FIG. 29 is an illustrative view for describing a method of displaying anevaluation result of a dark circle part according to the secondembodiment of the present invention.

FIGS. 30 to 34 are views for describing an evaluation algorithm appliedto a hue harmony part evaluation according to the second embodiment ofthe present invention.

FIG. 35 is an illustrative view for describing a method of displaying anevaluation result of a hue harmony part according to the secondembodiment of the present invention.

FIG. 36 is a view for describing an evaluation algorithm applied to alip part evaluation according to the second embodiment of the presentinvention.

FIG. 37 is an illustrative view for describing a method of displaying anevaluation result of a lip part according to the second embodiment ofthe present invention.

FIG. 38 is a view for describing an evaluation algorithm applied to ablemish part evaluation according to the second embodiment of thepresent invention.

FIG. 39 is an illustrative view for describing a method of displaying anevaluation result of a blemish part according to the second embodimentof the present invention.

FIG. 40 is an illustrative view for describing a method of displaying amakeup evaluation result according to the second embodiment of thepresent invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Hereinafter, embodiments will be described in detail with reference tothe accompanying drawings, however, the same elements are designated bythe same reference numerals, and repeated description thereof will beomitted. Suffixes “module” and “part” for elements used in the followingdescriptions are given or used just for convenience in writing thespecification, and do not have meanings or roles distinguishable betweenthem. In addition, in describing embodiments of the present disclosure,when detailed description of a known function is deemed to unnecessarilyblur the gist of the present disclosure, the detailed description willbe omitted. Further, accompanying drawings are only for easilyunderstanding embodiments disclosed in the present disclosure, and thetechnical spirit disclosed in the present disclosure are not limited bythe accompanying drawings, and it should be understood that the presentinvention includes all modifications, equivalents, and alternativesfalling within the spirit and scope of the claims.

It should be understood that, although the terms first, second, and thelike may be used herein to describe various elements, these elements arenot limited by these terms. The terms are only used to distinguish oneelement from another.

It should be understood that, when an element is referred to as being“connected” or “coupled” to another element, the element may be directlyconnected or coupled to the other element or intervening elements may bepresent. In contrast, when an element is referred to as being “directlyconnected” or “directly coupled” to another element, there are nointervening elements present.

Elements referred to in singular may be number one or more, unless thecontext clearly shows otherwise.

It should be further understood that the terms “comprises,”“comprising,” “includes,” and/or “including,” when used herein, specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

Next, a makeup evaluation system and an operation method thereofaccording to an embodiment of the present invention will be describedwith reference to FIGS. 1 to 40.

Fist, FIG. 1 is a block diagram illustrating a configuration of a makeupevaluation system according to an embodiment of the present invention.

Referring to FIG. 1, the makeup evaluation system according to anembodiment of the present invention may include a mobile terminal 10, anapplication server 200, and a makeup server 100.

The mobile terminal 10 may request a makeup evaluation. The mobileterminal 10 may request the makeup evaluation in association with atleast one makeup image, and may display a makeup evaluation result.

The application server 200 may be an element used for an applicationoperation for the makeup evaluation, and may store information necessaryfor the application operation for the makeup evaluation.

The application server 200 may transmit and receive a signal and datato/from at least one of the mobile terminal 10 and the makeup server 100according to execution of the makeup evaluation application.

The makeup server 100 may store data necessary for the makeupevaluation. For example, the makeup server 100 may store a data foridentifying each face part, an evaluation algorithm for evaluatingmakeup, and the like.

The makeup server 100 may evaluate the makeup based on the stored data,or transmit information necessary for the makeup evaluation to themobile terminal 10 or the application server 200. The makeup server 100may transmit an evaluation result signal including evaluation resultinformation of the makeup to the mobile terminal 10.

The mobile terminal 10, the application server 200, and the makeupserver 100 may transmit and receive signals to/from each other.

The mobile terminal 10 may transmit a makeup evaluation request signalto the application server 200, and when the application server 200receives the makeup evaluation request signal, it is possible totransmit a makeup image corresponding to the received makeup evaluationrequest signal to the makeup server 100.

According to one embodiment, when the makeup server 100 receives themakeup evaluation request signal, it is possible to evaluate makeup of areceived image based on the stored data and transmit an evaluationresult to the application server 200. The application server 200 maytransmit the evaluation result to the mobile terminal 10.

However, according to the embodiment, the application server 200 and themakeup server 100 may transmit and receive signals to/from the mobileterminal 10 as a single server, not separately. For example, theapplication server 200 may be included in the makeup server 100. In thiscase, the mobile terminal 10 may transmit the makeup evaluation requestsignal to the makeup server 100, and the makeup server 100 may evaluatethe makeup to transmit an evaluation result data to the mobile terminal10.

According to another embodiment, when the makeup server 100 receives amakeup evaluation request signal, it transmits data related to thereceived makeup evaluation request signal to the mobile terminal 10, andthe mobile terminal 10 evaluates the makeup based on the received data.

The mobile terminal 10 described in the present disclose may include amobile phone, a smart phone, a computer, a notebook computer, a tabletPC, a wearable device, a digital TV, a digital signage, a display deviceprovided in a store selling beauty-related products such as cosmetics,and a smart mirror provided in a home or a store.

FIG. 2 is a block diagram for describing a mobile terminal according toan embodiment of the present invention.

A mobile terminal 10 may include a wireless communication unit 11, aninput unit 12, a camera 13, a display unit 14, a memory 15, a powersupply unit 16, and a control unit 17. As described above, elementsshown in FIG. 2 are illustrative elements to help in understanding ofthe mobile terminal according to the present invention. The mobileterminal may have more or fewer elements than the elements listed above.

Hereinafter, each of the elements of the mobile terminal 10 will bedescribed in more detail.

The wireless communication unit 11 may include one or more modules forenabling wireless communication between the mobile terminal 10 andanother mobile terminal 10, or between the mobile terminal 100 and anexternal server. Specifically, the wireless communication unit 11 mayinclude at least one of a broadcast receiving module, a mobilecommunication module, a wireless internet module, a short distancecommunication module, and a location information module.

The wireless communication unit 11 may transmit and receive signalsto/from the another mobile terminal 10 or the external server. Forexample, the wireless communication unit 11 may transmit and receivesignals to/from at least one of an application server 200 and a makeupserver 100.

The input unit 12 may receive data or an instruction from a user. Theinput unit may receive an input signal via a mechanical key, a touchkey, voice recognition, or the like. The data or the instructionreceived via the input unit 12 may be processed as a control instructionto transmit to another element.

The camera 13 may receive a video signal input. A video signal includesa still image such as a photograph, a moving image, and the like.Accordingly, the camera 13 may receive the video signal input byphotographing the photograph, the moving image, or the like. Forexample, the camera 13 may photograph a facial image of the user.

The display unit 14 displays (outputs) information processed by themobile terminal 10. For example, the display unit 14 may display acontent received via the wireless communication unit 11, a content inputvia the input unit 12, or the like on a screen as the content providedto the user. In addition, the display unit 14 may display screeninformation of an application program driven by the mobile terminal 10.

Alternatively, the display unit 14 may display an image that is beingphotographed or photographed via the camera 13. For example, the displayunit 14 may display the facial image photographed via the camera 13.

In addition, the display unit 14 may display result information ofevaluating the makeup based on the photographed facial image.

Meanwhile, the display unit 151 may form a mutual layer structure with atouch sensor or may be integrally formed, thereby realizing a touchscreen. Such a touch screen may function as the input unit 12 and mayprovide an output interface between the mobile terminal 10 and the user.

The memory 15 stores data supporting various functions of the mobileterminal 10. The memory 15 may store a plurality of application programsor applications driven at the mobile terminal 10, data for operation ofthe mobile terminal 10, and instructions. At least a part of theapplications may be downloaded from the external server via the wirelesscommunication. Alternatively, at least a part of the applicationprograms may be present on the mobile terminal 10 at a time of shipmentfor basic functions (e.g., incoming call, outgoing call function,message receiving and sending function) of the mobile terminal 10.

Meanwhile, at least one of the application programs may be anapplication for the makeup evaluation.

The power supply unit 16 receives external power or internal power andsupplies power to each of the elements included in the mobile terminal10. The power supply unit 190 may include a battery, and the battery maybe an internal battery or a replaceable battery.

The control unit 17 controls an overall operation of the mobile terminal10. Specifically, the control unit 17 may control an operation of eachof the elements configuring the mobile terminal 10 or the operationrelated to the application program. The control unit 17 may processsignals, data, information, etc. input or output via the elements, ormay drive the application program stored in the memory 15 to provide orprocess appropriate information or a function to the user. The controlunit 17 may control at least a part of the elements, or may combine atleast two of them with each other to operate.

At least a part of the elements described with reference to FIG. 2 mayoperate in cooperation with each other to realize an operation, acontrol, or a control method of a mobile terminal according to variousembodiments will be described below. In addition, the operation, thecontrol or the control method of the mobile terminal may be realized onthe mobile terminal by driving of at least one application programstored in the memory 15.

Next, FIG. 3 is a block diagram for describing a makeup server accordingto a first embodiment of the present invention.

A makeup server 100 may be composed of a makeup DB management unit 110,a makeup evaluation unit 120, a control unit 130, and a wirelesscommunication unit 140.

First, the makeup DB management unit 110 will be described.

The makeup DB management unit 110 may include a makeup theme acquisitionunit 111, a makeup image acquisition unit 112, a score data generationunit 113, a makeup evaluation DB 114, and a makeup score learning unit115.

The makeup theme acquisition unit 111 determines a makeup theme throughdata analysis or a user input. The overall balance of makeup isimportant. In addition, the makeup that is in vogue changes according tothe trend of the times. Accordingly, the makeup theme acquisition unit111 may acquire a makeup theme by analyzing data existing on-line.Alternatively, the makeup theme acquisition unit 111 may receive amakeup theme input from a user to acquire the makeup theme.

The makeup image acquisition unit 112 receives a plurality of pieces ofmakeup image data which is the basis of makeup evaluation. Specifically,the makeup image acquisition unit 112 may receive a plurality of piecesof makeup image data classified according to the makeup theme. Inaddition, the makeup image acquisition unit 112 may acquire a no makeupimage together with a makeup image for the theme.

The makeup image received via the makeup image acquisition unit 112 maybe stored in the makeup evaluation DB 114.

The score data generation unit 113 generates makeup score data includinga makeup image and a corresponding makeup score thereto. The makeupimage of the makeup score data may be received via the makeup imageacquisition unit 112. The makeup score of the makeup score data may beformed based on an evaluation of a makeup specialist. Specifically, themakeup score data may be generated based on an input for the makeupevaluation of the makeup specialist. For example, the makeup score maybe input by the makeup specialist for each facial image. In addition,the makeup score may include a score calculated by the makeup server 100itself by machine learning.

In addition, the score data generation unit 113 may tune the makeupscore data to lower an error rate of the makeup evaluation system. Inaddition, the score data generation unit 113 may correct reliability ofthe makeup score data to acquire the objectivity of the makeupevaluation system.

The makeup evaluation DB 114 stores the makeup score data generated viathe score data generation unit 113. The makeup score data may be tuned,or the reliability thereof may be corrected.

In addition, the makeup evaluation DB 114 may store, together with themakeup score data generated via the score data generation unit 113, thescore data calculated in association with a new image. In this way, themakeup score learning unit 115 may perform a machine learning of amakeup score calculation method by using the makeup evaluation DB 114storing the makeup score data.

The makeup score learning unit 115 performs the machine learning of themakeup score calculation method based on the makeup evaluation DB 114.Specifically, the makeup score learning unit 115 may perform the machinelearning of the makeup score calculation method so as to be similar to amethod that a makeup specialist actually evaluates.

Next, the makeup evaluation unit 120 will be described in detail.

The makeup evaluation unit 120 may include a facial image acquisitionunit 121, a makeup analysis unit 122, and a makeup score output unit123.

The facial image acquisition unit 121 receives a facial image to besubjected to makeup evaluation. Specifically, the facial imageacquisition unit 121 may receive the facial image to be subjected to themakeup evaluation via the wireless communication unit 140.

The makeup analysis unit 122 analyzes the makeup of the facial imagereceived by the facial image acquisition unit 121. The makeup analysisunit 122 may analyze the makeup of each face region included in thefacial image. For example, the makeup analysis unit 122 may analyze themakeup through a method of comparing image data included in the facialimage and the makeup score data. That is, the makeup analysis unit 122may analyze the makeup based on statistical values of the makeup scoredata. A detailed method will be described later.

The makeup score output unit 123 calculates a makeup score of the facialimage based on a makeup analysis result. The makeup score output unit123 may calculate a makeup total score and a score for each face region.

The control unit 130 controls the overall operation of the makeup server100. Specifically, the control unit 130 may control operations of themakeup DB management unit 110, the makeup evaluation unit 120, and thewireless communication unit 140.

The wireless communication unit 140 may transmit and receive datato/from the outside. For example, the wireless communication unit 140may receive image data from a mobile terminal 10 or an applicationserver 200. The wireless communication unit 140 may transmit thereceived image data to the makeup DB management unit 110 or the makeupevaluation unit 120.

Meanwhile, embodiments described below may be implemented in a recordingmedium readable by a computer or a similar device by using, for example,software, hardware, or a combination thereof.

Next, an operation method of a makeup evaluation system according to afirst embodiment of the present invention will be described withreference to FIG. 4. FIG. 4 is a ladder diagram illustrating anoperation method of the makeup evaluation system according to the firstembodiment of the present invention.

First, the makeup theme acquisition unit 111 of the makeup server 100may determine a theme of makeup (S101).

According to one embodiment of the present invention, the makeup themeacquisition unit 111 may determine the theme of makeup via wirelesscommunication.

Specifically, the makeup theme acquisition unit 111 may acquirebeauty-related data on-line. The beauty-related data may include makeupsearch terms, uploaded makeup-related content, sales volume of makeupproducts, and the like. The makeup theme acquisition unit 111 mayanalyze the acquired beauty-related data for each makeup theme todetermine the makeup theme based on data amount. For example, the makeuptheme acquisition unit 111 may acquire three makeup styles in descendingorder of data amount to determine the acquired three makeup styles as amakeup theme.

Through such a method, the makeup theme acquisition unit 111 has aneffect of easily acquiring a trendy makeup theme.

According to another embodiment of the present invention, the makeuptheme acquisition unit 111 may determine the makeup theme by receivingan input signal.

Specifically, a user may input an arbitrary makeup theme to the makeupserver 100. The makeup theme acquisition unit 111 may acquire the makeuptheme corresponding to the input data to determine the makeup theme.

Through such a method, there is an effect that the makeup server 100 mayreflect a makeup theme in vogue off-line.

The makeup theme acquisition unit 111 may determine at least one makeuptheme through the first or second embodiment. For example, the makeuptheme acquisition unit 111 may determine A makeup, B makeup, and Cmakeup. A makeup may be a natural makeup, B makeup may be a lovelymakeup, and C makeup may be a smoky makeup, but this is merelyillustrative.

An embodiment for determining the makeup theme described above isillustrative, and the makeup theme acquisition unit 111 may determinethe makeup theme through other methods.

Meanwhile, the makeup theme acquisition unit 111 may acquire makeupcriteria together when acquiring the makeup theme. The makeup criteriamay refer to at least one feature that distinguishes makeup for themakeup theme. The makeup criteria may be subsequently used as aguideline in a step of receiving image data and a step of analyzing themakeup.

Next, the makeup image acquisition unit 112 may receive image datacorresponding to a determined makeup theme (S103).

The makeup image acquisition unit 112 may receive image datacorresponding to a makeup theme from the outside. For example, themakeup image acquisition unit 112 may receive image data correspondingto a makeup theme from an external storage medium, a mobile terminal, oran external server.

The makeup image acquisition unit 112 may receive a plurality of piecesof makeup image data for each makeup theme. For example, the makeupimage acquisition unit 112 may receive image data corresponding to Amakeup, image data corresponding to B makeup, and image datacorresponding to C makeup.

Meanwhile, the makeup image acquisition unit 112 may classify andreceive image data by a group. That is, the makeup image acquisitionunit 112 may receive the makeup theme image data from each groupclassified into a plurality of groups.

Next, FIG. 5 is an illustrative view for describing a method ofreceiving image data by a makeup server according to an embodiment ofthe present invention.

An image classification table 500 shown in FIG. 5 shows a distributionof the image data received via the makeup image acquisition unit 112. A1to A5, B1 to B5, C1 to C5 and D1 to D5 refer to a set of the receivedimage data.

Specifically, A1, A2, B1, B2, C1, C2, D1, and D2 are sets of image datacorresponding to a first group, and are sets of image data received toform a bottom category (lower, middle and lower) of the makeupevaluation DB.

A3, A4, B3, B4, C3, C4, D3 and D4 are sets of image data correspondingto a second group, and are sets of image data received to form a middlecategory (middle, middle and upper) of the makeup evaluation DB.

A5, B5, C5, and D5 are sets of image data corresponding to a thirdgroup, and are sets of image data received for constructing a topcategory (upper) of the makeup evaluation DB.

Thus, the makeup image acquisition unit 112 may acquire the A makeupimage, the B makeup image, the C makeup image, and the no makeup imageof each of the people included in the first through third groups havingdifferent scores. The A makeup image, the B makeup image, and the Cmakeup image are image data which are the basis of the makeup themeevaluation, respectively. The no makeup image may be image data used forprocessing the bottom point in a step of analyzing the makeup.

The first group may represent the general public, the second group mayrepresent a beauty-related industry person, and the third group mayrepresent a makeup specialist, but this is merely illustrative.

Thus, when the image data is classified and received by the makeup themeand group, there is an effect that a makeup analysis is more accuratelyperformed. In addition, there is an effect of providing a guidelinecapable of analyzing and evaluating the makeup accurately inconsideration of a photographing angle, a lighting, and the like, whichare control variables that may affect the makeup analysis.

Meanwhile, the makeup image acquisition unit 112 may receive a makeupimage other than the A makeup, the B makeup, and the C makeup. That is,the makeup image acquisition unit 112 may acquire a makeup image of atheme different from a determined makeup theme. This is image data forprocessing makeup that is out of the theme or is broken in balanceregardless of the completion of makeup as a zero-point.

FIG. 4 will be described again.

The score data generation unit 113 may generate makeup score data basedon the received image data (S105).

The score data generation unit 113 may generate the received image dataand score data including a score corresponding to each image data. Thatis, the score data generation unit 113 may convert the image data intothe score data.

Next, FIG. 6 is an illustrative view for describing makeup score dataaccording to the first embodiment of the present invention.

Makeup score data 600 shown in FIG. 6 includes image data and scorescorresponding to each image data. The score corresponding to the imagedata may be subdivided by region. For example, as shown in FIG. 6, eachimage data may include a score for each of the regions which are a baseregion, an eyebrow region, an eye region, a lip region, a blusher andshading region. However, each region is merely illustrative.

The makeup score data 600 shown in FIG. 6 shows only two pieces of imagedata corresponding to the A makeup and scores corresponding thereto, butthe score data generation unit 113 generates score data including allthe image data received in step S103.

The score data generation unit 113 may generate score data by receivinga score input for a region corresponding to each image data. Forexample, at least one makeup specialist may input a score for eachregion of the image data to the makeup server 100. The score datageneration unit 113 may generate makeup score data based on the scoredata input to the makeup server 100. The makeup score data shown in FIG.6 is displayed as a numerical value such as 5, 3.5, 4, etc., but this ismerely illustrative, and the makeup score data may be divided intoupper, middle and upper, middle, middle and lower, lower, and so on.

The makeup score data 600 represents features of makeup for each makeuptheme. Specifically, the makeup score data 600 represents differentscores depending on the theme of makeup, even for the same makeup image.In addition, even if the same makeup is applied, the score changesdepending on the face shape, eyes, etc. included in the image.Therefore, the makeup score data 600 includes a plurality of pieces ofmakeup image data, and includes scores for each region distinguishedaccording to a makeup theme.

When the makeup score data 600 is used, in the case of makeup image datathat is not related to the makeup theme, the score corresponding theretomay be calculated to be zero point.

Thus, when the makeup image is received and the score data is generated,the score data based on the evaluation of the specialist may begenerated. Accordingly, reliability of the makeup evaluation isimproved. In addition, makeup-related big data may be constructed.

FIG. 4 will be described again.

The score data generation unit 113 may tune makeup score data (S107).

The score data generation unit 113 may tune the makeup score data toimprove reliability of the generated makeup score data. Morespecifically, the score data generation unit 113 may tune the score dataso as to calculate the same makeup score, when a plurality of facialimages are photographed at different photographing angles orillumination. A method of tuning the makeup score data may be asfollows.

In association with the first image data received in step S103, themakeup image acquisition unit 112 may re-receive second image datacorresponding to the first image data. The second image data may beimage data different from the first image data, and may include a newlyproduced makeup image and a newly photographed no makeup image. That is,the second image data may refer to image data that is the same as thefirst image data in that it is a makeup performed by the same person,but may be recognized as different makeups depending on photographingangles or illumination, or the like.

Therefore, the score data generation unit 113 may tune the makeup scoredata such that a score calculated by the first image data and a scorecalculated by the second image data are the same.

Next, referring to FIGS. 7 and 8, an operation of tuning makeup scoredata will be described as an example.

FIGS. 7 and 8 are illustrative views for describing a method of tuningmakeup score data according to a first embodiment of the presentinvention.

First, referring to FIG. 7, first image data 71 and second image data 72are images of similar makeups. However, the first image data 71 and thesecond image data 72 are photographed at different photographing angles.A score data generation unit 113 may tune the makeup score data suchthat a score calculated by the first image data 71 and a scorecalculated by the second image data 72 are equal.

For example, the score data generation unit 113 may form the first imagedata 71 and the second image data 72 into one group to tune the samescore to be calculated. Alternatively, the score data generation unit113 may adjust the score calculated by the first image data 71 and thescore calculated by the second image data 72 to be equal through theimage data tuning.

Next, referring to FIG. 8, first image data 81 is makeup image data, andsecond image data 82 is no makeup image data of the same person. In thiscase, a score data generation unit 113 may tune makeup score data suchthat a score calculated for the second image data 82 is the lowestpoint.

Specifically, the score data generation unit 113 may recognize makeup ofthe first image data 81 and the second image data 82, respectively. Thescore data generation unit 113 may calculate a score of the makeuprecognized based on makeup score data 600 when the makeup is recognizedas in the first image data 81. On the other hand, when the makeup is notrecognized as in the second image data 82, the score data generationunit 113 may tune the makeup score data so as to calculate the lowestpoint.

As described above, there is an effect that quality of a makeupevaluation system may be improved by tuning the makeup score data suchthat the score data generation unit 113 reflects image data, aphotographing angle, an illumination at the time of photographing,identification of no makeup, etc.

FIG. 4 will be described again.

The score data generation unit 113 may correct reliability of makeupscore data (S109).

The control unit 130 may receive new image data not included in themakeup score data. The score data generation unit 113 may determinewhether a score of the received new image data is calculated withouterror based on the makeup score data. Hereinafter, a specific method ofcorrecting the reliability of the makeup score data will be described.

According to an embodiment of the present invention, a score datageneration unit 113 may calculate a makeup score corresponding to a newimage, and may acquire an image similar to the new image from makeupscore data.

The score data generation unit 113 may determine whether a scorecorresponding to the new image is calculated within a predeterminederror rate with the score of the similar image included in the makeupscore data. The score data generation unit 113 may correct a score ofrelated image data included in the makeup score data based on adetermination result.

Alternatively, according to another embodiment of the present invention,a score data generation unit 113 may acquire a first score which is amakeup score corresponding to a new image calculated based on makeupscore data. In addition, the score data generation unit 113 may acquirea second score which is a makeup score corresponding to a new imagebased on an input for makeup evaluation of a makeup specialist.

The score data generation unit 113 may compare the first score and thesecond score acquired in association with the same image. As a result ofcomparison, the score data generation unit 113 may determine whether thefirst score and the second score are different from each other by apredetermined range or more.

The score data generation unit 113 may receive feedback corresponding tothe comparison result from the makeup specialist when the first scoreand the second score are different from each other by the predeterminedrange or more.

The feedback may include a reason for a gap between the first score andthe second score. For example, the feedback may include information forcorrecting the first score or the second score, image recognitioninformation, or opinion information of the makeup specialist.

The score data generation unit 113 may correct the score of the imagedata included in the makeup score data based on the received feedback.

The method for correcting the reliability of the makeup score mayfurther include other methods in addition to the first to secondembodiments exemplified above.

The present invention has an effect that an error rate of the makeupscore data may be lowered and the reliability may be improved bycorrecting the makeup score as described above.

The control unit 130 may store the makeup score data (S111).

The control unit 130 may store the generated makeup score data. Inaddition, it is possible to store the makeup score data that has beentuned or corrected for reliability.

First, a makeup evaluation database according to an embodiment of thepresent invention will be described.

As described with reference to FIG. 6, a makeup evaluation databaseaccording to an embodiment of the present invention may store makeupscore data for each facial image. Accordingly, the makeup evaluationdatabase may be formed such that a makeup facial image and a score foreach region corresponding thereto are arranged.

Next, a makeup evaluation database according to another embodiment ofthe present invention will be described with reference to FIG. 9.

As shown in FIG. 9, the makeup evaluation database according to anotherembodiment of the present invention may store such that partial imagesare arranged by dividing a face region and a score. Accordingly, themakeup evaluation database may be formed such that the face region isdivided, the score is subdivided for each face region, and the partialimages are arranged in the score of the subdivided face region.

The makeup evaluation database described above is illustrative and maybe formed in a different form.

FIG. 4 will be described again.

The makeup server 100 may evaluate a makeup image by forming a makeupevaluation database.

First, the mobile terminal 10 transmits a facial image to theapplication server 200 (S113), and the application server 200 maytransmit the facial image received from the mobile terminal 10 to themakeup server 100 (S113).

The wireless communication unit 140 of the makeup server 100 may receivethe facial image from the application server 200.

The mobile terminal 10 may transmit a makeup evaluation request signalto the application server 200 via a makeup evaluation application. Themobile terminal 10 may display a screen for transmitting the makeupevaluation request signal.

FIG. 10 is an illustrative view for describing a screen for transmittinga makeup evaluation request signal according to a first embodiment ofthe present invention.

A display unit 14 of a mobile terminal 10 may display a makeupevaluation request screen as shown in FIG. 10.

Referring to FIG. 10, the makeup evaluation request screen may include amakeup theme item 1001, a facial image selection icon 1002, a facialimage window 1003, and an evaluation icon 1004.

The makeup theme item 1001 is an item for selecting a makeup theme.Makeup evaluation may vary depending on the makeup theme. Accordingly, acontrol unit 17 of the mobile terminal 10 may set the makeup theme viathe makeup theme item 1001.

The facial image selection icon 1002 is an item for selecting a facialimage to request a makeup evaluation. According to one embodiment of thepresent invention, the control unit 17 of the mobile terminal 10 maycontrol the display unit 14 so as to display a photographing screenusing a camera 13 when an instruction to select the facial imageselection icon 1002 is received. The camera 13 may photograph a face onwhich makeup is applied. The control unit 17 may display thephotographed facial image on the facial image window 1003.

According to another embodiment of the present invention, a control unit17 of a mobile terminal 10 may display at least one still image storedin a memory 15 when an instruction to select a facial image selectionicon 1002 is received. Alternatively, the control unit 17 may identifyan image including a face from the still image stored in the memory 15to display the still image including at least one face. The control unit17 may receive an instruction to select any one facial image from atleast one still image displayed on a display unit 14. The control unit17 may display the selected facial image on a facial image window 1003.

The facial image window 1003 is a window for previewing a facial imagefor which makeup evaluation is requested. Any one of the facial imagesphotographed via a camera 13 or stored in the memory 15 may be displayedin the facial image window 1003. A user may confirm whether the face tobe requested for the makeup evaluation is correct via the facial imagewindow 1003.

An evaluation icon 1004 is an icon for executing a makeup evaluationrequest. When an instruction to select the evaluation icon 1004 isreceived, the control unit 17 may transmit a makeup evaluation requestsignal to an application server 200. That is, the control unit 17 maycontrol a wireless communication unit 11 to transmit the makeupevaluation request signal including the facial image to the applicationserver 200.

The application server 200 may transmit the makeup evaluation requestsignal to a makeup server 100. Accordingly, a wireless communicationunit 140 of the makeup server 100 may receive the makeup evaluationrequest signal including the facial image from the application server200.

According to an embodiment, a mobile terminal 10 may transmit a makeupevaluation request signal directly to a makeup server 100.

The makeup evaluation request signal may further include a makeup theme,user information, and the like in addition to the facial image.

FIG. 4 will be described again.

The makeup analysis unit 122 of the makeup server 100 may analyze makeupof a received facial image (S115).

The facial image acquisition unit 121 may receive the facial image fromthe wireless communication unit 140. The makeup analysis unit 122 mayanalyze the makeup of the facial image received by the facial imageacquisition unit 121.

Next, FIG. 11 is an illustrative view for describing a method ofanalyzing a facial image by a makeup server according to a firstembodiment of the present invention.

A makeup analysis unit 122 may detect each region of a face to analyzemakeup. Specifically, according to one embodiment of the presentinvention, the makeup analysis unit 122 may preprocess a received facialimage. The makeup analysis unit 122 may divide the preprocessed facialimage into a plurality of regions, and may compare the divided regionswith pre-stored face region images to detect eyes, nose, mouth, and thelike.

According to another embodiment of the present invention, a makeupanalysis unit 122 may recognize each region of a face by using apre-trained model. The pre-trained model utilizes a part of aconventional convolutional neural network (CNN) model. The pre-trainedmodel may be used to learn a facial picture to recognize eyes, nose,mouth, and the like. Using the pre-trained model, it is possible toreduce a problem of overfitting that may occur when an amount of dataused for analysis is small.

As shown in FIG. 11, the makeup analysis unit 122 may recognize eyeregions 1151 and 1152, a nose region 1153, and mouth regions 1154 and1155 of a facial image 1100. The makeup analysis unit 122 may analyze amakeup evaluation region based on the recognized eye regions, noseregion, and mouth regions. That is, the makeup analysis unit 122 mayanalyze a base, eyebrow, eyes, lips, blusher and shading makeup of thefacial image 1100.

Next, FIG. 12 is an illustrative view for describing a method ofanalyzing makeup of a facial image by a makeup analysis unit accordingto a first embodiment of the present invention.

A makeup analysis unit 122 may compare the facial image received from amobile terminal 10 with a plurality of images included in a makeupevaluation database 114. The makeup analysis unit 122 may extract atleast one piece of image data similar to the received facial image fromthe makeup evaluation database 114.

In particular, the makeup analysis unit 122 may extract image datasimilar to the received facial image for each makeup region.Specifically, the makeup analysis unit 122 extracts at least one pieceof image data including a base similar to the base of the facial image,and at least one piece of image data including an eyebrow similar to theeyebrow of the facial image.

The makeup analysis unit 122 may acquire a score corresponding to theextracted image data to generate a makeup analysis graph 1200 as shownin FIG. 12. The makeup analysis graph 1200 shows a score distribution ofthe extracted image data.

Specifically, the makeup analysis unit 122 may map a score acquired inassociation with at least one piece of image data extracted with asimilar base to a score region of a base region 1201. Likewise, themakeup analysis unit 122 may map a score acquired in association with atleast one piece of image data extracted with similar eyebrows to a scoreregion of an eyebrow region 1202. The makeup analysis unit 122 maygenerate the makeup analysis graph 1200 by mapping scores to all of aneye region 1203, a lip region 1204, and a blusher and shading region1205.

In this manner, the makeup analysis unit 122 may generate the makeupanalysis graph 1200 to analyze makeup of the facial image. However, itis illustrative and the makeup analysis unit 122 may analyze the makeupthrough other methods.

FIG. 4 will be described again.

The makeup score output unit 123 of the makeup server 100 may calculatea makeup score of a facial image based on a makeup analysis result(S117).

The makeup score output unit 123 may calculate the makeup score of thefacial image based on a makeup analysis graph 1200.

Specifically, the makeup score output unit 123 may calculate and acquirea score having the highest score mapped for each region in the makeupanalysis graph 1200.

For example, referring to FIG. 12, the makeup score output unit 123 maycalculate and acquire 5 points for a score of a base region 1201, 9points for a score of an eyebrow region 1202, and 3 points for a scoreof an eye region 1203, 4.5 points for a score of a lip region 1203, 8points for a score of a blusher and shading region 1205.

The makeup score learning unit 115 of the makeup server 100 may learnthe facial image and the makeup score corresponding thereto (S119).

The makeup score learning unit 115 may machine learn the facial imageand the makeup score corresponding thereto. In particular, the makeupscore learning unit 115 may learn a method of calculating the makeupscore by using deep learning technology.

The deep learning technology is a part of machine learning technology,which uses artificial neural network techniques in which several layersof artificial neurons are stacked and connected between input andoutput.

That is, the makeup score learning unit 115 may machine learn the methodof calculating the makeup score by using the pre-stored makeup scoredata and the calculated makeup score.

In particular, the makeup score learning unit 115 may learn the facialimage and the makeup score corresponding thereto by using aconvolutional neural network (CNN). The CNN consists of one or severalconvolutional layers and general artificial neural network layersstacked thereon, and further utilizes weights and pooling layers.Because of this structure, the CNN may fully utilize input data of atwo-dimensional structure.

The makeup score learning unit 115 may machine learn the method ofcalculating the makeup score by adding a feature of a newly recognizedfacial image to the existing makeup evaluation database 114 by using theconvolutional neural network.

Therefore, the makeup score learning unit 115 may machine learn themethod of calculating the makeup score by adding a score of a newlycalculated facial image to the existing makeup score data generatedbased on an input for makeup evaluation of a makeup specialist.

As described above, when the makeup score learning unit 115 learns themakeup score, there is an effect that it is possible to evaluatesimilarly to an actual evaluation of the makeup specialist when a newmakeup image is given. Thus, there is an effect that it is possible toprovide a more reliable makeup evaluation service to a user.

The makeup score learning unit 115 may control so as to store thelearned makeup score in the makeup evaluation database.

Next, FIG. 13 is an illustrative view for describing a regeneratedmakeup evaluation database according to a first embodiment of thepresent invention.

The regenerated makeup evaluation database will be described using themakeup evaluation database 114 according to an embodiment describedabove.

As shown in FIG. 13, the makeup evaluation database 114 may furtherstore a newly calculated facial image score data 1302 in existing data1301 based on evaluation of a makeup specialist.

A control unit 130 may calculate a more objective makeup score by addinga newly calculated facial image score data to the makeup evaluationdatabase 114.

FIG. 4 will be described again.

The wireless communication unit 140 of the makeup server 100 transmits acalculated makeup score to the application server 200 (S120), and theapplication server 200 may transmit a received makeup score to themobile terminal 10 (S121).

The wireless communication unit 11 of the mobile terminal 10 may receivea makeup score from the application server 200. According to anembodiment, the mobile terminal 10 may receive the makeup score directlyfrom the makeup server 100.

The display unit 14 of the mobile terminal 10 may display the receivedmakeup score.

Next, FIGS. 14A and 14B and FIGS. 15 to 18 are illustrative views fordescribing makeup scores according to various embodiments of the presentinvention.

First, FIGS. 14A and 14B are illustrative views for describing a makeupscore screen according to an embodiment of the present invention.

A display unit 14 may display a makeup evaluation result screen as shownin FIGS. 14A and 14B. Specifically, the makeup score screen shown inFIG. 14A shows a makeup score evaluated with a makeup theme selected bya user, and the makeup score screen shown in FIG. 14B shows a makeupscore according to a makeup theme evaluated with the highest score.

First, each element configuring the makeup evaluation result screen willbe described.

The makeup evaluation result screen may include a facial image window1401, a makeup theme window 1402, a total score window 1403, a scorewindow by region 1404, and a makeup reevaluation icon 1405.

The facial image window 1401 includes a facial image analyzed by amakeup server 100. Thus, a user may reconfirm whether an intended facialimage is properly evaluated.

The makeup theme window 1402 shows the makeup theme on which the makeupevaluation is based. The makeup evaluation may be different depending onthe makeup theme even for the same facial image. Therefore, it showswhether the user has selected the makeup theme correctly.

The total score window 1403 shows a total score of the makeup evaluationresult of the facial image. For example, the total score window 1403 mayshow an average value of scores for each face region. Thus, the user mayconfirm his or her makeup result with one index.

The score window by region 1404 shows a result of evaluating makeup bydividing the facial image into regions. Thus, there is an effect thatthe user may easily know which region's makeup should be complemented.

The makeup reevaluation icon 1405 is an icon for receiving a makeupevaluation by using a new facial image. The control unit 17 may displaya makeup evaluation request screen as shown in FIG. 10 as it receives aninstruction to select the makeup reevaluation icon 1405.

The mobile terminal 10 displays a makeup evaluation result screen asdescribed above, and may provide an evaluation service similar to anevaluation by a makeup specialist.

According to an embodiment of the present invention, as shown in FIG.14A, a mobile terminal 10 may display a makeup evaluation result screenevaluated with a selected makeup theme.

Specifically, when a makeup server 100 receives the makeup themeselected by a user, the makeup server 100 may calculate a makeup scoreof a facial image according to the selected theme. In this case, themobile terminal 10 may display the makeup theme selected by the user ina makeup theme window 1402, and may display a score according to themakeup theme selected in a total score window 1403 and a score window byregion 1404.

According to another embodiment of the present invention, as shown inFIG. 14B, a mobile terminal 10 may display a makeup evaluation resultscreen with a makeup theme evaluated with the highest score.

Specifically, a makeup server 100 may calculate a makeup score of atleast one facial image for each makeup theme. The makeup server 100 mayacquire a makeup theme that shows the highest score among the scorescalculated for each makeup theme. The makeup server 100 may transmit allthe makeup scores for each makeup theme to the mobile terminal 10, ormay transmit only the highest score and the makeup theme correspondingto the highest score to the mobile terminal 10.

In this case, the mobile terminal 10 may display the makeup themeevaluated with the highest score in a makeup theme window 1402, and maydisplay the score according to the makeup theme evaluated with thehighest score in a total score window 1402 and a score window by region1404.

According to still another embodiment of the present invention, a mobileterminal 10 may simultaneously display a score according to a makeuptheme selected by a user and a score according to a makeup themeevaluated with the highest score.

Next, FIG. 15 is a view for describing an effect of a makeup theme on amakeup evaluation according to the first embodiment of the presentinvention.

As described in FIGS. 14A and 14B, a display unit 14 of a mobileterminal 10 may display a makeup evaluation result screen.

The makeup evaluation result screen of FIG. 15 is a makeup evaluationresult screen when the same facial image is targeted as compared withFIGS. 14A and 14B, but the makeup theme is different. That is, a facialimage window 1501 includes the same facial image as compared with FIGS.14A and 14B, but a makeup theme 1502 is different from each other.

Accordingly, it may be seen that the makeup evaluation result isdifferent. That is, it may be seen that a total score window 1503 and ascore window by region 1404 show different scores as compared with FIGS.14A and 14B.

Thus, an effect that a user may learn not only a makeup skill but alsomakeup suitable for the makeup theme is expected.

Next, FIG. 16 is a view for describing a score window by regionaccording to the first embodiment of the present invention.

A score window by region 1604 shows a score for each region based on amakeup theme. Accordingly, the score window by region 1604 may show adifferent score depending on a makeup region. In particular, inassociation with any one face region, there may be regions that aretreated as zero point when it is determined that makeup is completelydifferent from the makeup theme.

Thus, there is an effect that it is possible to guide a user to makeupby a face region.

Next, FIG. 17 is a view for describing a makeup balance evaluationaccording to the first embodiment of the present invention.

Referring to FIG. 17, it may be confirmed that a total score 1703 showszero point, but each region of a score window by region 1704 is not zeropoint. This may show that a makeup balance of entire face does notmatch. That is, a makeup evaluation system may evaluate not only makeupby face region but also the makeup balance of the entire face.

Next, FIG. 18 is a view for describing a no makeup evaluation resultaccording to the first embodiment of the present invention.

Referring to FIG. 18, both a total score window 1803 and a score windowby region 1804 show the lowest point. This is a case in which a face ofa facial image window 1801 is determined as no makeup. As describedabove, reliability of a makeup evaluation system may be improved bycalculating the lowest point corresponding to the face of the no makeup.

Next, FIG. 19 is a block diagram for describing a makeup serveraccording to the second embodiment of the present invention.

The makeup server 100 may include a makeup DB management unit 110, amakeup evaluation unit 120, a control unit 130, and a wirelesscommunication unit 140.

First, the makeup DB management unit 110 will be described.

The makeup DB management unit 110 may store various data related to amakeup evaluation.

The makeup DB management unit 110 may store at least one evaluationalgorithm applied to a face region for evaluating makeup. Here, the faceregion may be a face region included in an image, which may refer to aface region detected by a region detection unit 124 described later. Inaddition, the face region may include a region including an entire faceand each face part region configuring a face. For example, the faceregion may include at least one of an entire face region, an eyebrowregion, an eye region, a nose region, a cheek region, a forehead region,a chin region, a lip region, and the like.

The evaluation algorithm may be an algorithm that uses an RGB value ofat least one pixel configuring the face region included in the image.That is, the image may be an image represented by the RGB value, and theevaluation algorithm may be an algorithm that uses the RGB value of thepixel configuring the face region.

In addition, the evaluation algorithm may be an algorithm that convertsthe RGB value of at least one pixel configuring the face region includedin the image into a Lab color value, and uses the converted Lab colorvalue. That is, the evaluation algorithm may be an algorithm thatconverts an image represented by the RGB value into a Lab color spaceand evaluates makeup via the Lab color value. Since the Lab color valuedoes not change depending on an output medium, it is possible to performconsistent evaluation regardless of the output medium when theevaluation algorithm using the Lab color value is applied, and it isadvantageous that reliability of the makeup evaluation may be secured.

In addition, the makeup DB management unit 110 may store a score table(see FIG. 34) used for the makeup evaluation. Specifically, the scoretable may include a plurality of first sample colors and a plurality ofsecond sample colors. Here, the first sample color may be a sample colorrepresenting skin color, and the second sample color may be a samplecolor representing lip color, blusher color, or eye shadow color.

Each of the plurality of first sample colors and the plurality of secondsample colors may be mapped, and score data may be mapped to a pair ofthe first sample color and the second sample color. That is, the scoretable may be composed of the score data mapped to any one of a pluralityof first sample colors and a plurality of second sample colors.

As described above, the score table may be used when evaluating a hueharmony of the makeup. For example, a makeup analysis unit 122 maydetect a first color and a second color in the face region of a user,and may evaluate the hue harmony of the makeup based on the first colorand the second color. Specifically, the makeup analysis unit 122searches for the same color as the first color from the plurality offirst sample colors, searches for the same color as the second colorfrom the plurality of second sample colors, and acquires a score mappedto a searched pair of colors, thereby evaluating the hue harmony.

In addition, according to one embodiment, the score table may be a tablegenerated based on an input for a makeup evaluation of a makeupspecialist. That is, the score table may be a table in which makeupspecialists have previously input scores for color combinations.

When the makeup analysis unit 122 described later evaluates the makeupby using the table generated based on the input for the makeupevaluation of the makeup specialist, there is an advantage that it ispossible to provide the user with a makeup evaluation result based onexpertise. Accordingly, reliability of a makeup evaluation system may beincreased.

Next, the makeup evaluation unit 120 will be described in detail.

The makeup evaluation unit 120 may be composed of the region detectionunit 124 and the makeup analysis unit 122.

The region detection unit 124 may acquire a facial image included inphotographs or a moving images. Specifically, the region detection unit124 may receive the photographs or the moving images via the wirelesscommunication unit 140, and may detect the facial image to be targetedto makeup evaluation from the photographs or the moving images.

In addition, the region detection unit 124 may detect each region of theface from the facial image. For example, the region detection unit 124may detect at least one of the eyebrow region, the eye region, the noseregion, the cheek region, the lip region, and the chin region.

For example, the region detection unit 124 may detect the face and eachpart of the face via a face recognition algorithm.

In addition, the region detection unit 124 has an advantage that theface and each part of the face may be recognized more accurately throughthe deep learning technology in face recognition.

The makeup analysis unit 122 analyzes makeup of the face region and eachpart of the face acquired by the region detection unit 124. For example,the makeup analysis unit 122 may analyze the makeup of the face regionand each region of the face based on the score table and the evaluationalgorithm stored in the makeup DB management unit 110. A detailed methodwill be described later.

According to an embodiment, the makeup analysis unit 122 calculates themakeup score of the facial image based on the makeup analysis result.For example, the makeup analysis unit 122 may calculate a makeup totalscore and a score by the face region, respectively.

The control unit 130 controls an overall operation of the makeup server100. Specifically, the control unit 130 may control operations of themakeup DB management unit 110, the makeup evaluation unit 120, and thewireless communication unit 140.

The wireless communication unit 140 may transmit and receive datato/from the outside. For example, the wireless communication unit 140may receive image data from a mobile terminal 10 or an applicationserver 200. The wireless communication unit 140 may transmit thereceived image data to the makeup DB management unit 110 or the makeupevaluation unit 120.

Meanwhile, embodiments described below may be implemented in a recordingmedium readable by a computer or similar device by using, for example,software, hardware, or a combination thereof.

Next, FIG. 20 is a ladder diagram illustrating an operation method of amakeup evaluation system according to the second embodiment of thepresent invention.

In FIG. 20, for convenience of explanation, the mobile terminal 10transmits and receives signals to/from the makeup server 100, and it isassumed that the application server 200 described in FIG. 1 is includedin the makeup server 100.

The control unit 17 of the mobile terminal 10 may acquire an image(S11).

The control unit 17 may acquire the image via the wireless communicationunit 11 or the camera 13. The wireless communication unit 11 may receivethe image from the outside. The camera 13 may acquire the image byphotographing photographs or moving images

A user may transmit or input a makeup facial image to the mobileterminal 10 in order to a makeup evaluation. For example, the user maytransmit the image stored outside to the mobile terminal 10, or mayphotograph a face that is makeup with the camera 13 of the mobileterminal 10.

The control unit 17 of the mobile terminal 10 may receive a requestinstruction for the makeup evaluation (S11).

The control unit 17 may receive the request instruction for the makeupevaluation via the input unit 12. The input unit 12 may receive therequest instruction for the makeup evaluation after receiving aninstruction to select at least one image.

The user may input a request for the makeup evaluation in the input unit12 after selecting the image for which the makeup evaluation is desired.

In addition, the control unit 17 may further receive a makeup themeselection instruction via the input unit 12 when receiving the requestinstruction for the makeup evaluation. The makeup theme may includenatural, lovely, smoky, or the like. The makeup evaluation may bedifferent depending on the makeup theme. Therefore, for a more accuratemakeup evaluation, the control unit 17 may receive the instruction toselect the makeup theme when receiving the request instruction for themakeup evaluation.

The control unit 17 of the mobile terminal 10 may transmit a makeupevaluation request signal to the makeup server 100 (S15).

The control unit 17 may control so as to transmit the makeup evaluationrequest signal to the makeup server 100 via the wireless communicationunit 11.

The makeup evaluation request signal may include image data. That is,the control unit 17 may transmit the makeup evaluation request signalincluding image data corresponding to the image acquired in step S11 tothe makeup server 100.

The makeup evaluation request signal may be a signal requesting a makeupevaluation corresponding to a face included in an image according to theimage data.

The wireless communication unit 140 of the makeup server 100 may receivethe makeup evaluation request signal.

The control unit 130 of the makeup server 100 may analyze the image dataincluded in the makeup evaluation request signal. Specifically, theimage data included in the makeup evaluation request signal may be datamodulated for image transmission. The control unit 130 may restore theimage data included in the makeup evaluation request signal into animage.

The control unit 130 of the makeup server 100 may detect a predeterminedregion from the image received via the makeup evaluation request signal(S17).

The control unit 130 may set in advance at least one evaluation part tobe a target of the makeup evaluation. The control unit 130 may detect atleast one region corresponding to the evaluation part from the image.

For example, the control unit 130 may set as the evaluation part to bethe target of the makeup evaluation at least one of an eyebrow part, adark circle part, a hue harmony part, a lip part, and a blemish part.However, the evaluation parts listed above are merely an example for theconvenience of description, and the present invention is not limitedthereto.

The control unit 130 may detect at least one region of an eyebrow regionfor evaluating the eyebrow part, a dark circle region for evaluating thedark circle part, a hue harmony region for evaluating the hue harmonypart, a lip region for evaluating the lip part, and a blemish region forevaluating blemish part from the received image.

At this time, each region such as eyebrow region, dark circle region,and the like is not limited to a corresponding part, and may include atleast one part according to an evaluation algorithm by region. Forexample, the eyebrow region is not limited to an eyebrow part, and mayinclude the eyebrow part and a nose part. Evaluating the eyebrow regionis not only for evaluating a shape and color of the eyebrow butevaluating in consideration of harmony of the entire face and theeyebrow part. The detection parts corresponding to each of the regionswill be described in detail through the evaluation algorithm by regiondescribed later.

The control unit 130 may evaluate by applying the evaluation algorithmfor each region to at least one region detected (S19).

The control unit 130 may apply different evaluation algorithms accordingto the detected region. For example, the control unit 130 may apply afirst evaluation algorithm to the eyebrow region and apply a secondevaluation algorithm to the dark circle region.

As described above, according to an embodiment of the present invention,instead of applying the same evaluation algorithm to a plurality ofdetected regions and evaluating them consistently, there is an advantagethat the makeup evaluation may be more precisely evaluated by applyingdifferent evaluation algorithms according to the detected region.

Next, at least one evaluation algorithm applied to each of the regionsdetected by the control unit 130 in step S17 will be described.

First, FIGS. 21 to 25 are views for describing an evaluation algorithmapplied to an eyebrow part evaluation according to the second embodimentof the present invention. FIG. 26 is an illustrative view for describinga method of displaying an evaluation result of the eyebrow partaccording to the second embodiment of the present invention.

According to an embodiment of the present invention, the makeup DBmanagement unit 110 of the makeup server 100 may store an evaluationalgorithm for evaluating the eyebrow part. The control unit 130 maydetect an eyebrow region via a region detection unit 124, and may applythe evaluation algorithm to the eyebrow region detected via a makeupanalysis unit 122 in step S17.

The evaluation algorithm for evaluating the eyebrow part may include aplurality of algorithms, and each algorithm may evaluate the eyebrowpart differently. For example, the evaluation algorithm for evaluatingthe eyebrow part may include an algorithm for evaluating an eyebrowlength, an algorithm for evaluating a horizontal degree, an algorithmfor evaluating an eyebrow front length, and an algorithm for evaluatingeyebrow color uniformity.

When applying the evaluation algorithm to the eyebrow region, the makeupanalysis unit 122 may analyze and evaluate all the eyebrow length, thehorizontal degree, the eyebrow front length, and the eyebrow coloruniformity.

A method of evaluating the eyebrow length of the eyebrow region by thecontrol unit 130 will be described with reference to FIG. 21.

The region detection unit 124 may detect a first point 501 which is anouter end of any one eye in an image, and a second point 502 which is anouter end of a nose. At this time, the region detection unit 124 maydetect a right end of the nose when an outer end point of a right eye isdetected, and a left end of the nose when an outer end point of a lefteye is detected.

The makeup analysis unit 122 may acquire a straight line 510 connectingthe first point 501 and the second point 502.

The makeup analysis unit 122 may detect a third point 503 which is anouter end of the eyebrow, and may calculate a distance d1 between thethird point 503 and the straight line 510.

The makeup analysis unit 122 may determine appropriateness of theeyebrow length through the calculated distance d1. For example, themakeup analysis unit 122 may determine that the eyebrow length is‘short’ when the calculated distance d1 is less than a first distance,and may determine that the eyebrow length is ‘proper’ when thecalculated distance d1 is longer than the first distance and less than asecond distance, and may determine that the eyebrow length is ‘long’when the calculated distance d1 is longer than the second distance.However, such a determination method is merely illustrative, and thepresent invention is not limited thereto.

A method of evaluating the horizontal degree of the eyebrow region bythe control unit 130 will be described with reference to FIG. 22.

The region detection unit 124 may detect a first point 601 which is aninner end of the eyebrow and a second point 602 which is an outer end ofthe same eyebrow based on any one eyebrow in an image.

The region detection unit 124 may acquire a straight line 610 connectingthe first point 601 and the second point 602, and may calculate an angleθ between the straight line and a horizontal line 620.

The makeup analysis unit 122 may determine the appropriateness of thehorizontal degree of the eyebrow through the calculated angle θ.

For example, the makeup analysis unit 122 may determine that thehorizontal degree of the eyebrow is ‘straight’ when the calculated angleθ is equal to or less than a first angle, and may determine that thehorizontal degree of the eyebrow is ‘general type’ when the calculatedangle θ is greater than the first angle and equal to or less than asecond angle, and may determine that the horizontal degree of theeyebrow is ‘arch type’ when the calculated angle θ is greater than thesecond angle. However, such a determination method is merely an example,and the present invention is not limited thereto.

In addition, the makeup analysis unit 122 may determine an eyebrow typeaccording to the horizontal degree of the eyebrow such as ‘straightline’, ‘general type’ or ‘arch type’, and may calculate a score of aneyebrow shape according to each type determined. For example, datashowing the eyebrow shape according to the eyebrow type may be stored inadvance. The makeup analysis unit 122 compares the data of the eyebrowshape according to the determined eyebrow type with the data of theeyebrow shape acquired from the image. As a result of comparison, as adifference between the stored data and the data acquired from the imageis smaller, the score may be determined by a manner of calculating theeyebrow score higher.

Referring to FIG. 23, a method for the control unit 130 to evaluate theeyebrow front length of the eyebrow region will be described.

The region detection unit 124 may detect a first point 701 which is aninner end of an eyebrow and a second point 702 which is an outer end ofa nose based on any one eyebrow in an image. At this time, the regiondetection unit 124 may detect a right end of the nose when an inner endpoint of a right eyebrow is detected, and a left end of the nose when aninner end point of a left eyebrow is detected.

The makeup analysis unit 122 may acquire a straight line 710 passingthrough the second point 702 in the vertical direction and a distance d2between the straight line 710 and the first point 701.

The makeup analysis unit 122 may determine the appropriateness of theeyebrow front length through the calculated distance d2. For example,the makeup analysis unit 122 may determine that the eyebrow front lengthis ‘short’ when the calculated distance d2 is equal to or less than afirst distance, and may determine that the eyebrow front length is‘proper’ when the calculated distance d2 is longer than the firstdistance and equal to or less than a second distance, and may determinethat the eyebrow front length is ‘long’ when the calculated distance d2is longer than the second distance. However, such a determination methodis merely an example, and the present invention is not limited thereto.

According to the method described in FIGS. 21 to 23, there is anadvantage that it is possible to perform a makeup evaluation thatreflects a size of the eyes, a size of the nose, and the like, which aredifferent for each person. That is, the eyebrow is not consistentlydetermined that 5 cm is appropriate, but there is an advantage that themakeup may be evaluated in consideration of different facialcharacteristics such as a length of the person's eyes, a length of thenose, and a position of the eyebrow.

A method for evaluating uniformity of eyebrow color in the eyebrowregion by the control unit 130 will be described with reference to FIGS.24 and 25. The uniformity of the eyebrow color may be an item showingwhether the eyebrow color is uniformly made up.

The control unit 130 may perform the eyebrow determination operation inorder to determine the uniformity of the eyebrow color.

The region detection unit 124 may detect first to fifth points 801 to805 in the eyebrow. Specifically, the region detection unit 124 maydetect the first point 801 which is an outer end of the eyebrow and thesecond point 802 which is an inner end of the eyebrow, the third point803 which is a middle of the first point 801 and the second point 802 ofthe eyebrows, and the fourth point 804 which is a middle of the firstpoint 801 and the third point 803 of the eyebrow and the fifth point 805which is a middle of the second point 802 and the third point 803.

As shown in FIG. 24A, the makeup analysis unit 122 may acquire a curveline 810 connecting the first to fifth points 801 to 805.

As shown in FIG. 24B, the makeup analysis unit 122 may acquire avertical line 820 at each point of the curve line along the curve line810, and may extract an image value at the vertical line 820. Here, theimage value may include RGB values, and the vertical line 820 may be astraight line having a predetermined length.

The makeup analysis unit 122 may acquire a maximum value among the RGBvalues extracted along the vertical line 820, and determine a pointhaving the maximum value and an image value within a predetermined ratiofrom the maximum value as the eyebrow. For example, the makeup analysisunit 122 may acquire a maximum value 126 when the extracted image valuesare 40, 41, 120, 122, 126, 43, 40, and points in which the image valueswithin 20% of the maximum value 126 are 120 and 122 and a point in whichthe image value is 126 may be determined as the eyebrow.

The makeup analysis unit 122 may perform the eyebrow determinationoperation described above in a gray channel, a red channel, and a bluechannel of the image, respectively.

When FIG. 25A is an original image, the makeup analysis unit 122 mayperform the eyebrow determination operation on the gray channel todetermine a first region 901 as an eyebrow as shown in FIG. 25B. Inaddition, the makeup analysis unit 122 may perform the eyebrowdetermination operation on the red channel to determine a second region902 as an eyebrow as shown in FIG. 25C.

The makeup analysis unit 122 may measure similarity between the firstregion 901 and the second region 902. The makeup analysis unit 122 maymeasure the similarity through an area of an overlapping region of thefirst region 901 and the second region 902. That is, the makeup analysisunit 122 may calculate the higher the similarity as the area of theoverlapping region between the first region 901 and the second region902 is wider, and the lower the similarity as the area of theoverlapping region is narrower.

The makeup analysis unit 122 may determine the eyebrow uniformitythrough the calculated similarity. For example, the makeup analysis unit122 may determine that the eyebrow uniformity is ‘non-uniform’ when thecalculated similarity is equal to or less than a first reference value,and may determine that the eyebrow uniformity is ‘uniform’ when thecalculated similarity exceeds a second reference value. However, such adetermination method is merely an example, and the present invention isnot limited thereto.

Meanwhile, when an area of the second region 902 determined as theeyebrow by the red channel is equal to or less than a reference area,the makeup analysis unit 122 may perform the eyebrow determinationoperation in a blue channel image to determine a third region 903 as theeyebrow as shown in FIG. 25D. The makeup analysis unit 122 may determinethe eyebrow uniformity as described above by measuring the similarity ofthe first region 901 and the third region 903.

The wireless communication unit 140 may transmit an evaluation resultsignal to a mobile terminal 10 after evaluating makeup, and a displayunit 14 of the mobile terminal 10 may display the evaluation result.

FIG. 26 may be an illustrative view showing a makeup evaluation resultof an eyebrow part. The display unit 14 may display evaluation resultsof an eyebrow length, a horizontal degree, an eyebrow front length, andeyebrow uniformity. However, a method of showing the evaluation resultshown in FIG. 26 is merely illustrative.

Next, FIGS. 27 and 28 are views for describing an evaluation algorithmapplied to a dark circle part evaluation according to the secondembodiment of the present invention, and FIG. 29 is an illustrative viewfor describing a method of displaying an evaluation result of a darkcircle part according to an embodiment of the present invention.

The region detection unit 124 may detect a plurality of points in theeye region. For example, the region detection unit 124 may detect firstto fourth points 1101 to 1104 in the eye region, and the first point1101 may be an outer end point of the eye, the second point 1102 may bean inner end point of the eye, the third point 1103 may be an upper endpoint of the eye, and the fourth point 1104 may be a lower end point ofthe eye.

The makeup analysis unit 121 may calculate a horizontal distance 11 ofthe eye by measuring a straight line distance connecting the first andsecond points 1101 and 1102, and may calculate a vertical distance 12 ofthe eye by measuring a straight line distance connecting the third andfourth points 1103 and 1104.

The makeup analysis unit 121 may acquire a reference line 1110 based onthe first to fourth points 1101 to 1104 and the horizontal distance 11and the vertical distance 12. For example, the makeup analysis unit 121may acquire the reference line 1110 having a length corresponding to apredetermined ratio of the horizontal distance 11 at a position spacedapart from the third point 1103 downward by the vertical distance 12. Alength of the reference line 1110 may be 80% of the horizontal distance11, but it is merely illustrative.

Referring to FIG. 28, the makeup analysis unit 121 may extract a maximumvalue among RGB values of a left ⅓ region 1111 of the reference line1110, a maximum value among RGB values of a right ⅓ region 1112 of thereference line 1110, and a minimum value among RGB values of a centerhalf region 1113 of the reference line 1110.

The makeup analysis unit 121 may acquire a smaller value among theextracted two maximum values, and may calculate a difference between theacquired smaller value and the above-extracted minimum value. The makeupanalysis unit 121 may evaluate a degree of darkness of the dark circlesbased on the calculated difference.

According to the present invention, it is possible to detect a darkcircle target region through the first to fourth points 1101 to 1104 andthe eye distance. A surrounding skin color is acquired through the RGBvalues on both sides in the dark circle target region, and a color ofthe darkest part under the eyes is acquired through a central RGB value,and thus there is an advantage that it is possible to measure moreprecisely the darkness of the dark circle. That is, there is anadvantage that it is possible to evaluate whether the dark circle ismade up so as to be well covered to be similar to the surrounding skincolor, rather than simply measuring the dark circle.

Next, FIGS. 30 to 34 are views for describing an evaluation algorithmapplied to a hue harmony part evaluation according to the secondembodiment of the present invention, and FIG. 35 is an illustrative viewfor describing a method of displaying an evaluation result of a hueharmony part according to the second embodiment of the presentinvention.

First, the control unit 130 may control to extract skin color.Specifically, referring to FIG. 30A, the region detection unit 124 maydetect a nose region 3001 in a face included in an image. In particular,the region detection unit 124 may detect a nose tip region. The makeupanalysis unit 122 may extract a plurality of RGB color valuescorresponding to a plurality of points included in the nose region 3001,and may calculate an average value of the extracted RGB color values.The makeup analysis unit 122 may extract a color corresponding to thecalculated RGB average value as the skin color.

The makeup analysis unit 122 may distribute the extracted skin color ina Lab color space to detect a color closest to the extracted skin color,and may determine the detected color as the skin color. As shown in FIG.30B, the makeup DB management unit 110 stores a plurality ofrepresentative skin colors, and the makeup analysis unit 122 may acquirethe color closest to the detected skin color from the storedrepresentative colors, and the acquired color may be determined as theskin color. For example, in FIG. 30, the makeup analysis unit 122 maydetermine s5 as the skin color.

Next, the control unit 130 may control so as to extract a lip color.Specifically, referring to FIG. 31A, the region detection unit 124 maydetect a lip region 3101 in a face included in an image. In particular,the region detection unit 124 may detect a lower lip region. The makeupanalysis unit 122 may extract a plurality of RGB color valuescorresponding to a plurality of points included in the lip region 3101,and may calculate an average of the extracted RGB color values. Themakeup analysis unit 122 may extract a color corresponding to thecalculated RGB average value as the lip color.

The makeup analysis unit 122 may distribute the extracted lip color in aLab color space to detect a color closest to the extracted lip color,and may determine the detected color as the lip color. As shown in FIG.31B, the makeup DB management unit 110 stores a plurality ofrepresentative lip colors, and the makeup analysis unit 122 may acquirethe color closest to the detected lip color among the plurality ofrepresentative lip colors, and the acquired color may be determined asthe lip color. For example, in FIG. 31, the makeup analysis unit 122 maydetermine 17 as the lip color.

Next, the control unit 130 may control so as to extract a blusher color.Specifically, referring to FIG. 32A, the region detection unit 124 maydetect a cheek region 3201 from a face included in an image. The cheekregion 3201 may include both a left cheek region and a right cheekregion.

The makeup analysis unit 122 may perform an obstacle removal operationwhen extracting the blusher color. Here, the obstacle removal operationmay be an operation for minimizing a case in which the cheek region ishidden by hair or the like and the blusher color is determinedincorrectly. When the makeup analysis unit 122 performs the obstacleremoval operation, the makeup analysis unit 122 may remove a regionhaving a value smaller than a predetermined reference value afterconverting an image into a gray image, and for example, thepredetermined reference value may be 0.35, but it is merely an exampleand the present invention is not limited thereto. The makeup analysisunit 122 may extract a plurality of RGB color values corresponding toremaining regions except for the removed region in the cheek region3201, and may calculate an average value of the extracted RGB colorvalues. The makeup analysis unit 122 may extract a color correspondingto the calculated RGB average value as the blusher color.

The makeup analysis unit 122 may distribute the extracted blusher colorin a Lab color space to detect a color closest to the extracted blushercolor, and may determine the detected color as the blusher color. Asshown in FIG. 32B, the makeup DB management unit 110 stores a pluralityof representative blusher colors, and the makeup analysis unit 122 mayacquire the color closest to the detected blusher color among theplurality of representative blusher colors, and the acquired color maybe determined as the blusher color. For example, in FIG. 32, the makeupanalysis unit 122 may determine b8 as the blusher color.

Meanwhile, the makeup analysis unit 122 may also determine a valuehaving a large value of ‘a’ as a representative blusher color in the Labcolor space of the cheek region 3201.

Next, the control unit 130 may control so as to extract an eye shadowcolor.

Specifically, referring to FIG. 33, the region detection unit 124 maydetect a region above eyes 3301 from a face included in an image. Theregion above eyes 3301 may include both a region above the left eye anda region above the right eye.

The makeup analysis unit 122 may perform an obstacle removal operationas described above when extracting the eye shadow color. The makeupanalysis unit 122 may extract a plurality of RGB color valuescorresponding to remaining regions except for the region removed throughthe obstacle removal operation in the region above eyes 3301, and maycalculate an average of the extracted RGB color values. The makeupanalysis unit 122 may extract a color corresponding to the calculatedRGB average value as the eye shadow color. In particular, the makeupanalysis unit 122 may extract a left eye shadow color and a right eyeshadow color, respectively. The makeup analysis unit 122 may determine arepresentative shadow color based on the extracted eye shadow color.

According to one embodiment, the makeup analysis unit 122 may determinea representative shadow color in a different method according to amakeup theme. The makeup analysis unit 122 may determine a value havinga large value of ‘a’ as a representative shadow color in a Lab colorspace of the extracted left eye shadow color and right eye shadow colorwhen the makeup theme is natural or lovely. The makeup analysis unit 122may determine a value having a small value of 1′ as the representativeshadow color in the Lab color space of the extracted left eye shadowcolor and right eye shadow color when the makeup theme is smoky. This isbecause a recommended eye shadow color differs depending on the makeuptheme, and the representative shadow color is determined in a differentmethod according to the makeup theme, and thus there is an advantagethat it is possible to evaluate whether the makeup is well adapted tothe theme as well as whether the makeup is well done.

Next, a method of evaluating a hue harmony with a determined skin color,lip color, blusher color, and shadow color will be described.

The makeup DB management unit 110 may include a plurality of firstsample colors and a plurality of second sample colors, and may store ascore table in which score data is mapped to a pair of sample colorscomposed of any one of the plurality of first sample colors and any oneof the plurality of second sample colors.

For example, referring to FIG. 34A, the makeup DB management unit 110may store a skin-lip score table that maps a plurality of skin colorsand a plurality of lip colors and shows a score corresponding thereto.The makeup analysis unit 122 may search for the determined skin colorand lip color in the skin-lip score table, and may acquire the scoremapped to the searched skin color and lip color, and may determine theacquired score as a skin & lip harmony score.

Likewise, referring to FIG. 34B, the makeup DB management unit 110 maystore a skin-blusher score table that maps a plurality of skin colorsand a plurality of blusher colors and shows a score correspondingthereto. The makeup analysis unit 122 may search for the determined skincolor and blusher color in the skin-blusher score table, and may acquirethe score mapped to the searched skin color and blusher color, and maydetermine the acquired score as a skin & blusher harmony score.

Next, a method of determining a skin & eye shadow harmony score will bedescribed. The makeup analysis unit 122 may calculate a differencebetween the representative shadow color and the skin color determined bythe method described with reference to FIG. 33. Specifically, the makeupanalysis unit 122 calculates a difference of the ‘a’ value and adifference of the ‘L’ value between the representative shadow color andthe skin color, respectively, and may determine a score based on thecalculated difference of the ‘a’ value and difference of the ‘L’ value.Likewise, the makeup analysis unit 122 may determine the scoredifferently according to a makeup theme.

As described above, the makeup analysis unit 122 may determine a hueharmony analysis with the skin in the case of eye shadow differentlyfrom the case of the lip color and the blusher. This is because ablusher or a lip tends to be similar in color series even though makeupthemes are different, but in the case of eye shadow, the color seriesmay be completely different depending on the makeup theme. Accordingly,there is an advantage that it is possible to evaluate more precisely thehue harmony when determining the hue harmony part of the makeup.

Meanwhile, when extracting at least one of the skin color, the lipcolor, the blusher color, and the shadow color, the makeup analysis unit122 may determine it as zero point in the case of the skin color ofwhich a color is not extracted.

The wireless communication unit 140 may transmit the evaluation resultsignal to the mobile terminal 10 after evaluating the hue harmony part,and the display unit 14 of the mobile terminal 10 may display theevaluation result.

FIG. 30 may be an illustrative view showing the makeup evaluation resultfor the hue harmony part. The display unit 14 may display the evaluationresults of skin & lip harmony, skin & blusher harmony, and skin & eyeshadow harmony. However, the method of showing the evaluation resultshown in FIG. 30 is merely illustrative.

Next, FIG. 36 is a view for describing an evaluation algorithm appliedto a lip part evaluation according to the second embodiment of thepresent invention, and FIG. 37 is an illustrative view for describing amethod of displaying an evaluation result of a lip part according to thesecond embodiment of the present invention.

A region detection unit 124 may detect a lip region 2001 from a faceincluded in an image. The detected lip region may be as shown in FIG.36A.

A makeup evaluation unit 120 may evaluate lip uniformity and lip drynessin association with makeup of the lip region 2001. Here, the lipuniformity shows uniformity of the lip color, and may be an item showingwhether the makeup of the lip is uniformly well done. The lip drynessmay be an item showing whether the makeup of the lip is well done instate of being moist.

First, a method of evaluating the lip uniformity by the makeupevaluation unit 120 will be described. The makeup analysis unit 122 mayconvert the detected lip region 2001 into a Lab color space, and mayacquire an image of a reflection region of the lip region by setting athreshold value in an image in an space. For example, the makeupanalysis unit 122 may detect a region formed by pixels included in apredetermined range of value in the image in the space, and maydetermine the detected region as the reflection region.

FIG. 36B may be an illustrative view showing a reflection regiondetermined by the makeup analysis unit 122. It is illustrated such thata size of a reflection region 2002 is the largest in step 1, and thesize of the reflection region 2002 is decreased as it goes to step 5.

The makeup analysis unit 122 may calculate the size of the lip region inthe image as shown in FIG. 36A, and may calculate the size of thereflection region detected in the image as shown in FIG. 36B.

The makeup analysis unit 122 may calculate a ratio of the size of thereflection region to the size of the lip region. The makeup analysisunit 122 may evaluate the lip uniformity based on the calculated ratioof the size. That is, the makeup analysis unit 122 may evaluate highlythe lip uniformity in the case of the lip shown in step 1, and mayevaluate lower the lip uniformity as it goes to step 5.

Similarly, the makeup evaluation unit 120 may evaluate the lip dryness.

The makeup analysis unit 122 may detect the lip region, and may acquirethe lip region image 2001 as shown in FIG. 36A.

The makeup analysis unit 122 may acquire a filtered image adopting ahigh pass filter from the acquired lip region image. The makeup analysisunit 122 may acquire a mask image showing vertical wrinkles of the lipregion through threshold setting in an image in R space of the filteredimage. That is, the makeup analysis unit 122 may detect a regionconfigured by pixels in which the R value of the lip region is includedin a predetermined range, and may determine as a wrinkle region 2002showing the detected region. The wrinkle region 2002 may be acquiredstepwise similar to an example shown in FIG. 36B.

The makeup analysis unit 122 may calculate the size of the lip region inthe image as shown in FIG. 36A, and may calculate the size of thewrinkle region 2002 in the image as shown in FIG. 36B.

The makeup analysis unit 122 may calculate a ratio of the size of thewrinkle region to the size of the lip region. The makeup analysis unit122 may evaluate the lip dryness based on the calculated ratio of thesize. That is, the makeup analysis unit 122 may calculate greatly theratio of the size and evaluate highly the lip dryness in the case of thelip shown in step 1, and may calculate lower the ratio of the size andevaluate lower the lip dryness as it goes to step 5.

Although the reflection region 2002 and the wrinkle region 2002 aredescribed as the same in FIG. 36, it is merely one example for theconvenience of description, and the reflection region 2002 and thewrinkle region 2002 may be detected differently in one image, and thusthe lip uniformity and the lip dryness may be evaluated differently.

However, the above-described lip part evaluation method is merely anexample, and the present invention is not limited thereto.

The wireless communication unit 140 may transmit the evaluation resultsignal to the mobile terminal 10 after evaluating the lip part, and thedisplay unit 14 of the mobile terminal 10 may display the evaluationresult.

FIG. 37 may be an illustrative view showing the makeup evaluation resultfor the lip part. The display unit 14 may display the evaluation resulton the lip uniformity. The display unit 14 may display a scorecorresponding to lip uniformity and a score corresponding to lipdryness, respectively. However, the method of showing the evaluationresult shown in FIG. 37 is merely illustrative.

Next, FIG. 38 is a view for describing an evaluation algorithm appliedto a blemish part evaluation according to the second embodiment of thepresent invention, and FIG. 39 is an illustrative view for describing amethod of displaying an evaluation result of the blemish part accordingto the second embodiment of the present invention.

An image detection unit 121 may acquire an image, and may detect a faceregion included in an acquired image. For example, the image detectionunit 121 may detect the face region as shown in FIG. 38A.

The image detection unit 121 may detect a cheek region 2201 in thedetected face region, and the cheek region 2201 may include a left cheekregion and a right cheek region. For example, the image detection unit121 may detect the cheek region 2201 in the face region as shown in FIG.38B.

The image detection unit 121 may detect a chin region 2202 in thedetected face region. The makeup analysis unit 122 may convert all thepixels included in the chin region 2202 into a Lab space, and maycalculate an average value of each of L, a, and b in the converted Labspace to calculate the average Lab value of the skin.

The makeup analysis unit 122 may calculate the RGB average value of theskin by converting the average Lab value into the RGB value.

Next, the makeup analysis unit 122 may set a blemish target region.Specifically, the makeup analysis unit 122 may convert an imageincluding the face region into a Lab color space, and may acquire a gapimage corresponding to a difference between the converted Lab and theaverage Lab value of the skin calculated previously.

The makeup analysis unit 122 may acquire left and right gap imagescorresponding to differences between the pixels located on a side (leftor right) based on each of a plurality of pixels included in the gapimage, and may acquire upper and lower gap images corresponding todifferences between the pixels located above or below based on each ofthe plurality of pixels included in the gap image.

The makeup analysis unit 122 may acquire a color difference imagecorresponding to a sum of squares of the pixel values of the left andright gap images and squares of the pixel values of the upper and lowergap images. The makeup analysis unit 122 may acquire a target regioncomposed of points in which the pixel values in a color difference imageare larger than a predetermined threshold value.

The makeup analysis unit 122 may perform a morphological operation onthe target region to set a clustering region as a blemish target region2203 as shown in FIG. 38D.

The makeup analysis unit 122 may acquire heterogeneous points 2213,2223, and 2233 of which pixel values are different from each other bythe predetermined threshold value or more in the blemish target region2203. In particular, as shown in FIG. 38E, the makeup analysis unit 122may recognize the heterogeneous points 2213 and 2223 acquired in thecheek region 2201 as a blemish.

The makeup analysis unit 122 may detect a size of the cheek region 2201and sizes of the heterogeneous points 2213 and 2223 recognized as theblemish, respectively, and may calculate a ratio of the sizes of theheterogeneous points 2213 and 2223 to the size of the cheek region 2201.The makeup analysis unit 122 may evaluate skin uniformity based on thecalculated size ratio. For example, the makeup analysis unit 122 maydetermine as five points when the size ratio is between a firstreference value (e.g., 0%) and a second reference value (e.g., 5%), asthree points when the size ratio is between the second reference value(e.g., 5%) and a third reference value (e.g., 10%), and as one pointwhen the size ratio is between the third reference value (e.g., 10%) anda fourth reference value (e.g., 20%).

The skin uniformity shows whether the skin color of the face isuniformly made up, and may be an index showing whether the makeup coveris well done such that defects such as blemishes, dots, or wrinkles arenot seen.

The wireless communication unit 140 may transmit the evaluation resultsignal to the mobile terminal 10 after evaluating the blemish part, andthe display unit 14 of the mobile terminal 10 may display the evaluationresult.

FIG. 39 may be an illustrative view showing the makeup evaluation resultfor the blemish part. The display unit 14 may display the evaluationresult on the blemish. However, the method of showing the evaluationresult shown in FIG. 39 is merely illustrative.

FIG. 20 will be described again.

The makeup server 100 may transmit an evaluation result signal obtainedby evaluating the makeup to the mobile terminal 10 (S21).

As described above, scores evaluated for each of the detailed evaluationparts such as an eyebrow part, a dark circle part, a hue harmony part, alip part, and a blemish part, and the like may be summed up to derive amakeup total score. According to an embodiment, a ratio at which eachdetailed evaluation part contributes to the total score may be setdifferently according to a makeup theme. For example, when the makeuptheme is natural, the total score is calculated to be reflected at aratio of 60% for a score of the dark circle part and 10% for each scoreof the remaining the eyebrow part, the hue harmony part, the lip part,and the blemish part. When the makeup theme is smoky, the total scoremay be calculated to be reflected at a ratio of 35% for the hue harmonypart, 40% for the lip part, 15% for the eyebrow part, 5% for the darkcircle part, and 5% for the blemish part.

The display unit 14 of the mobile terminal 10 may display the makeupevaluation result based on the received evaluation result signal (S23).

The display unit 14 may display the makeup result as shown in FIG. 40.

That is, the display unit 14 may display scores for each of the makeupevaluation parts and the total score.

Alternatively, the display unit 14 may display the makeup evaluationresult as shown in FIGS. 26, 29, 35, 37, and 39. In particular, when anyone part of a plurality of evaluation parts as shown in FIG. 40 isselected, the display unit 14 may display the evaluation result as shownin FIG. 26, 29, 35, 37, or 39 by the detailed evaluation result of theselected part.

Meanwhile, although it has been described that the makeup server 100performs a makeup evaluation, it is merely an example for theconvenience of description. The mobile terminal 10 may acquire an imageto directly perform a makeup evaluation, and in this case, it mayreceive data related to the makeup evaluation from the makeup server100.

Meanwhile, the makeup evaluation system has been described above dividedinto the first embodiment according to FIGS. 3 to 18 and the secondembodiment according to FIGS. 19 to 40, but it is merely an example, andthe present invention is not limited to this. That is, the makeupevaluation system and the operation method thereof according to thefirst embodiment described with reference to FIGS. 3 to 18 may beconfigured in combination with the makeup evaluation system and theoperation method thereof according to the second embodiment describedwith reference to FIGS. 19 to 40.

For example, the makeup analysis unit 122 may output a makeup score byapplying the makeup score data as shown in FIG. 6 together with thealgorithm described with reference to FIGS. 21 to 25.

In addition, the display unit 14 may combine and display the makeupresult screen according to the first embodiment and the makeup resultscreen according to the second embodiment.

The present invention described above may be implemented ascomputer-readable codes in a medium on which a program is recorded. Thecomputer-readable medium includes all kinds of recording devices inwhich computer-readable data is stored. Examples of thecomputer-readable medium include a hard disk drive (HDD), a solid statedisk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, amagnetic tape, a floppy disk, and an optical data storage, etc. Inaddition, the computer may include a control unit of a diagnosis device,a control unit of a skin management server, or a control unit of amanufacturing apparatus. Accordingly, the above detailed descriptionshould not be construed in a limiting sense in all respects, and shouldbe considered as examples. The scope of the present invention should bedetermined by rational interpretation of the appended claims, andencompasses all alterations falling within the equivalent scope of theappended claims.

1. A makeup evaluation system comprising: a mobile terminal forphotographing an image and transmitting the photographed image to amakeup server; and a makeup server; wherein the makeup server comprises:a make-up DB management unit for storing at least one algorithm used formake-up evaluation, a region detection unit for detecting a face regionin the photographed image, a makeup analysis unit for evaluating makeupby applying the stored algorithm to the detected face region, and awireless communication unit for transmitting an evaluation result signalincluding information on the result of evaluating the makeup to themobile terminal, and wherein the mobile terminal displays the evaluationresult according to a received evaluation result signal, and the makeupserver evaluates makeup by applying different algorithms for each faceregion.
 2. The makeup evaluation system according to the claim 1,wherein the region detection unit detects a region corresponding to afirst part and a region corresponding to a second part of a faceincluded in the image, wherein the makeup analysis unit appliesdifferent algorithms to a region corresponding to the first part and aregion corresponding to the second part.
 3. The makeup evaluation systemaccording to the claim 1, wherein the at least one algorithm includes analgorithm using RGB values of at least one or more pixels constitutingthe face region.
 4. The makeup evaluation system according to the claim3, wherein the at least one algorithm includes an algorithm thatconverting RGB values of at least one or more pixels constituting theface region into Lab color values, and using the converted Lab colorvalues.
 5. The makeup evaluation system according to the claim 4,wherein the region detection unit detects a first region and a secondregion of the face region and obtains a first color corresponding to aLab color value of the first region and a second color corresponding toa Lab color value of the second region, the makeup analysis unitevaluates the color harmony of the makeup based on the first color andthe second color.
 6. The makeup evaluation system according to the claim5, wherein the first region is a region corresponding to a nose and thesecond region is a region corresponding to a cheek, a regioncorresponding to lips or a region corresponding to area above eyes. 7.The makeup evaluation system according to the claim 5, the makeup DBmanagement unit includes a score table in which score data is mapped toa pair of sample colors including any one of a plurality of first samplecolors and any one of a plurality of second sample colors, and themakeup analysis unit determines the same color as the first color amongthe plurality of first sample colors, determines the same color as thesecond color among the plurality of second sample colors, and obtainsthe score data mapped to the determined colors from the score table. 8.The makeup evaluation system according to the claim 7, wherein the scoretable includes a table generated based on an input for makeup evaluationby a makeup expert.
 9. The makeup evaluation system according to theclaim 3, wherein the region detection unit detects a lip region in theimage, and the makeup analysis unit calculates the size of the detectedlip region, obtains a wrinkle region composed of pixels having an Rvalue within a preset range among the lip region, calculates the size ofthe wrinkle region, and evaluates a dryness of lips through the ratio ofthe size of the detected lip region to the size of the wrinkle region.10. The makeup evaluation system according to the claim 4, wherein theregion detection unit detects a lip region in the image, and the makeupanalysis unit converts RGB values of pixels constituting the detectedlip region into Lab color values, obtains a reflective region composedof pixels having the L value within a preset range, calculates the sizeof the reflective region and evaluates the lip color through the ratioof the size of the lip region to the size of the reflection region. 11.The makeup evaluation system according to the claim 4, wherein themakeup analysis unit determines a skin color through an average of theLab color values of one area of the face region, converts RGB values ofpixels constituting the face region into Lab color values, obtains gapimage corresponds to the difference between the Lab color values and thedetermined skin color, and calculates a blemish ratio by detectingblemish target area through the gap image.
 12. The makeup evaluationsystem according to the claim 1, wherein the region detection unitdetects an eyebrow region, and the makeup analysis unit evaluateseyebrow makeup based on a distance or angle between two points in thedetected eyebrow region.
 13. The makeup evaluation system according tothe claim 3, wherein the region detection unit detects an eyebrowregion, and the makeup analysis unit evaluates a color of the eyebrowregion through RGB values corresponding to a vertical line passingthrough at least one point among the detected eyebrow region.
 14. Themakeup evaluation system according to the claim 3, wherein the regiondetection unit detects an eye region, and the makeup analysis unitevaluates a degree of dark circles through RGB values corresponding to ahorizontal line spaced apart from the detected eye region by apredetermined distance.
 15. A mobile terminal comprising: a memoryconfigured to store at least one algorithm used for make-up evaluation;a camera configured to photograph an image; and a control unitconfigured to detect a face region in the photographed image, evaluatemakeup by applying the stored algorithm to the detected face region, anddisplay information on the result of evaluating the makeup, wherein thecontrol unit evaluates makeup by applying different algorithms for eachface region.
 16. The mobile terminal according to the claim 15, whereinthe control unit detects a region corresponding to a first part and aregion corresponding to a second part of a face included in the image,and applies different algorithms to a region corresponding to the firstpart and a region corresponding to the second part.
 17. The mobileterminal according to the claim 15, wherein the at least one algorithmincludes an algorithm using RGB values of at least one or more pixelsconstituting the face region.
 18. The mobile terminal according to theclaim 17, wherein the at least one algorithm includes an algorithm thatconverting RGB values of at least one or more pixels constituting theface region into Lab color values, and using the converted Lab colorvalues.
 19. The mobile terminal according to the claim 18, wherein thecontrol unit detects a first region and a second region of the faceregion, obtains a first color corresponding to a Lab color value of thefirst region and a second color corresponding to a Lab color value ofthe second region, and evaluates the color harmony of the makeup basedon the first color and the second color.
 20. The mobile terminalaccording to the claim 19, wherein the first region is a regioncorresponding to a nose and the second region is a region correspondingto a cheek, a region corresponding to lips or a region corresponding toarea above eyes.